Systemic sclerosis (SSc) is a rare, complex rheumatic disease involving multiple organ systems with a frequently fatal outcome. It remains one of the most difficult rheumatic disease to manage, with limited effective therapies. There are several impediments to more rapid advances in understanding SSc pathogenesis and finding new treatments. First, the relative rarity of SSc and need of these patients for specialty clinical care has concentrated translational studies in select institutions having an adequate patient base and a program for sample/tissue collection. Thus many investigators have little or no access to patient samples/tissues. Even for investigators seeing relatively large numbers of patients, large sample sizes for proving associations between clinical disease and pathogenic features under study can prove elusive. Second, the heterogeneity of patient presentation and disease progression leads to fragmented approaches to understanding pathogenesis, different investigators studying different disease manifestations, for example, skin fibrosis compared to pulmonary arterial hypertension. Third, advanced technologies, such as microarray and proteomics are applied using different platforms, rendering interpretation of studies across different sites difficult. Empowered by a Consortia of SSc investigators formed to address these problems, this Core Center will leverage existing institutional resources to form four cores, providing patient samples and common platforms for advanced technologies designed to serve the broad clinical, translational basic scientific interests of Consortia Investigators. The Administrative Core (Core A), will provide structure, communication and enrichment of Core Investigators. Two cores (Cores B and C) will array pathological specimens from skin and lung, respectively, from SSc patients for rapid immunohistochemical evaluation of target proteins. Two cores will provide Consortia Investigators access to powerful Proteomic (Core D) and Microarray (Core E) technologies. All Cores will additionally use economy-of-scale and Core funding to provide services at a fraction of normal cost. In addition, the common platform and clinical data collected across cores will provide a large, common database for understanding clinical-pathological associations.